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Hands-on Foundations for Data Science and Machine Learning with Google Cloud Labs Specialization

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Learn Data Science & Machine Learning. Get Hands-On with Data Science & Machine Learning with Google Cloud
In this Google Cloud Labs Specialization, you’ll receive hands-on experience building and practicing skills in BigQuery and Cloud Data Fusion. You will start learning the basics of BigQuery, building and optimizing warehouses, and then get hands-on practice on the more advanced data integration features available in Cloud Data Fusion.

Learning will take place leveraging Google Cloud’s Qwiklab platform where you will have the virtual environment and resources need to complete each lab.

This specialization is broken up into 4 courses comprised of a series of courses:

BigQuery Basics for Data Analysts
Building Advanced Codeless Pipelines on Cloud Data Fusion
Data Science on Google Cloud
Data Science on Google Cloud: Machine Learning
You will even be able to earn a Skills Badge in one of these lab-based courses.
Applied Learning Project
This specialization leverages hands-on labs using our Qwiklabs platform. You can expect to gain practical hands-on experience with the concepts explained throughout each lab.

Learners will be able to practice:

Creating dataset partitions that will reduce cost and improve query performance.
Using macros in Data Fusion that introduce dynamic variables to plugin configurations so that you can specify the variable substitutions at runtime.
Building a reusable pipeline that reads data from Cloud Storage, performs data quality checks, and writes to Cloud Storage.
Using Google Cloud Machine Learning and TensorFlow to develop and evaluate prediction models using machine learning.
Implementing logistic regression using a machine learning library for Apache Spark running on a Google Cloud Dataproc cluster to develop a model for data from a multivariable dataset.
And much more!

Course Information

Estimated Time: Approximately 1 month to complete Suggested pace of 5 hours/week

Difficulty: Intermediate

Free

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Course Information

Estimated Time: Approximately 1 month to complete Suggested pace of 5 hours/week

Difficulty: Intermediate